LLM_Analyzer is an ambitious project designed to not only collect and curate data from various platforms like Reddit and YouTube but also to provide detailed analytics on the gathered data. The project will fetch, analyze, and present insights into the tendencies, trends, and patterns in the data, leveraging state-of-the-art data processing techniques.
- Data Collection: The system fetches data from platforms such as Reddit and YouTube. The data includes posts, comments, videos, and more.
- Database Design: Using MongoDB, the data is organized, stored, and indexed for efficient retrieval.
- Web Interface: A Flask-based web application is available for easy access and visualization of the database contents.
- Data Processing: The raw data from the database will undergo processing to filter out noise and irrelevant information.
- Analytics: The system will implement machine learning and statistical analysis to determine tendencies, sentiment analysis, and various other metrics.
- Visualization: Visual representations of the analysis, like graphs and charts, will provide users with understandable and actionable insights.
- Custom Reports: Users will be able to generate reports based on specific criteria, giving them the power to see the data in ways most relevant to their interests.
- Scheduled Summaries: Regular updates and summaries will keep stakeholders informed about the latest trends.
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Clone the repository:
git clone https://github.com/yourusername/LLM_Analyzer.git
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Navigate to the project directory:
cd LLM_Analyzer -
Install necessary dependencies:
pip install -r requirements.txt
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Start the Flask application:
python3 app.py
We welcome contributions! Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests.
This project is licensed under the MIT License - see the LICENSE.md file for details.
- Reddit API for enabling the data collection process.
- YouTube Data API for providing detailed metrics and data.
- MongoDB for efficient storage and retrieval.